Quartagno, M;
Grund, S;
Carpenter, J;
(2019)
jomo: A Flexible Package for Two-level Joint Modelling Multiple Imputation.
R Journal
, 9
(1)
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Abstract
Multiple imputation is a tool for parameter estimation and inference with partially observed data, which is used increasingly widely in medical and social research. When the data to be imputed are correlated or have a multilevel structure — repeated observations on patients, school children nested in classes within schools within educational districts — the imputation model needs to include this structure. Here we introduce our joint modelling package for multiple imputation of multilevel data, jomo, which uses a multivariate normal model fitted by Markov Chain Monte Carlo (MCMC). Compared to previous packages for multilevel imputation, e.g. pan, jomo adds the facility to (i) handle and impute categorical variables using a latent normal structure, (ii) impute level-2 variables, and (iii) allow for cluster-specific covariance matrices, including the option to give them an inverse-Wishart distribution at level 2. The package uses C routines to speed up the computations and has been extensively validated in simulation studies both by ourselves and others
| Type: | Article |
|---|---|
| Title: | jomo: A Flexible Package for Two-level Joint Modelling Multiple Imputation |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | https://journal.r-project.org/archive/2019/RJ-2019... |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology > MRC Clinical Trials Unit at UCL |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10078316 |
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